Construction and Evaluation of a Model of Natural Human
Motion based on Motion Diversity
Takashi Minato

Hiroshi Ishiguro

Asada Project, ERATO,
Japan Science and Technology Agency
2–1 Yamada-oka
Suita, Osaka 565–0871, Japan

Department of Adaptive Machine Systems,
Graduate School of Eigineering,Osaka University
2–1 Yamada-oka
Suita, Osaka 565–0871, Japan

minato@jeap.org
ABSTRACT
A natural human-robot communication is supported by a person’sinterpersonal behavior for a robot. The condition to elicit interpersonal behavior is thought to be related to a mechanism to support
natural communication. In the present study, we hypothesize that
motion diversity produced independently of a subject’s intention
contributes to the human-like nature of the motions of an androidthat closely resembles a human being. In order to verify this hypothesis, we construct a model of motion diversity through the observation of human motion, specifically, a touching motion. Psychological experiments have shown that the presence of motion diversity in android motion influences the impression toward the android.

Keywords
human motion model, natural motion, android

1.

INTRODUCTION

In order to develop a robot that can work in normal everyday
situations, it is necessary to discover the principles relevant to establishing and maintaining social interaction between humans androbots. Even if short-term human-robot interaction can be performed by implementing simple behaviors in a robot, it remains
difficult to realize long-term social interaction. In a previous study,
we explored the principles underlying natural human-robot communication through an android science approach [3].
Nass et al. [10] demonstrated that the human-computer relationship is fundamentally social and that a person’s social response toward computers is automatic in social situations. It is inferred fromtheir study that a person’s interpersonal responses subconsciously
expressed toward a robot (in other words, perceptual social illusion[4]) underlie the natural communication between the person and therobot. The condition to elicit interpersonal behavior must be related
to a mechanism to support natural communication. The android
science approach explores the boundary conditions to elicit subconscious interpersonal behavior toward an android from humans.

ishiguro@ams.eng.osaka-u.ac.jp
by investigating methods to make the android more humanlike.
Humanlike body motions are necessary to implement humanlike
behavior in an android. There have been several studies on thegeneration of humanlike motion, including studies on a model togenerate human motion trajectories based on a neurocomputational
approach [2, 15, 6, 13], a study on the control of a manipulator
based on a model of motion trajectories of a person’s arm [5], andstudies on a computer graphics (CG) animated characters, whichhave shown that noise in the motion makes the character’s motion
more humanlike [11, 1]. These studies successfully generated a humanlike motion. However, a humanlike motion specific to communication situations is not considered. The present study considers
the human-like nature of a person’s motion during interaction withother people.
A person generally does not produce exactly identical motion
when he/she repeats a behavior with the same intention. In contrast, a robot is able to repeat exactly identical motion with a purpose. A person’s motion is diverse in that the motion varies according to noises, mental and physical states, the social situation, andso on, even if the person’s intention does not change. We endow
an android with motion diversity in order to make the android behavior more humanlike. If a person consciously or subconsciously
attributes a cause of motion diversity in an android motion to suchthings as the android’s mental states, physical states, and the social
situations, the person has more humanlike impression toward theandroid.
We further consider the diversity of human motion. We divide a
person’s motion into (i) a motion that satisfies his/her intention and(ii) a motion change that is not relevant to the intention (a variationof the physical properties of the motion (i) such as its trajectory andvelocity). The motion diversity described in the previous paragraphmeans a diversity in the motion change. Motion generation models
involving a signal-dependent noise have been proposed in studies
related to the diversity of the motion change [14, 8]. This noisebased diversity cannot be controlled even if the subject consciously
attempts to control or suppress this diversity. In contrast, motion
diversity caused by such things as mental strain or hesitation canbe consciously controlled. We assume that the motion diversity
in an intentional motion influences the human-like nature of theandroid behavior, even if an observed motion change caused by thediversity is small.
The present paper hypothesizes that the motion change that is not
relevant to a subject’s intention and can be consciously controlled
influences the humanlike impression of the subject. In particular,
we focus on motion diversity in an intentional motion caused by
the social relationship between the subject and another person. The
present paper concretely takes up the motion of a person reaching2.5

Box low
Box high
Human shoulder
Human nose
Human brow

Figure 1: Gesture to be modeled. An subject reaches out andtouches another subject (top:box, bottom:another person).

Velocity [m/s]

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A MODEL OF HUMAN MOTION
DIVERSITY BASED ON DIFFERENCES
IN SOCIAL SITUATION

The present paper hypothesizes that motion diversity in an intentional motion independent of uncontrollable noise contributes to thehuman-like nature of the motion. In order to examine this hypothesis, we model the motion difference caused by the social relationship between two subjects in the motion of one subject reachingout and touching the other. It is, however, difficult to control thesocial relationship between two persons in an experiment. As theextreme case, we consider the difference between a person-object
relationship (Figure 1, top) and an interpersonal relationship (Figure 1, bottom). The person-object relationship is not social, but thispaper considers it as the least social relationship. We then constructa model of the difference in the subject’s arm movements in thesetwo cases.
In order to construct the model, we set up the situations shown in
Figure 1 and measured the subject’s arm movements with a motion
capture system (MAC 3D System, Motion Analysis Corporation).
The task of the subject was to reach out with the right hand andtouch a box or a female experimenter in front of the subject. The
hand position of the subject was measured by attaching a marker tothe back of the hand. The sampling time was 60 Hz. The subject
touched the left shoulder, nose, and forehead of the experimenterand two spots on the box, the heights of which are the same as thoseof the shoulder and forehead (box low and box high). The subjects
were seven male students. Some of the subjects were familiar withthe female experimenter and others were not. All subject touched
the target in the order of box low, box high, left shoulder, nose,and forehead, once for each target (total of thirty-five trials). The
subjects were told to touch the target and return their hand to theinitial position.
The analysis is not for the purpose of finding differences in motion common to all subjects because the motion variation is caused
by individuality in some cases. It is sufficient to find a feature
to differentiate a subject-person relationship (interpersonal case)from a subject-object relationship (impersonal case) within a sub-

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Time [sec]Figure 2: Example of a subject’s hand velocity (subject 1).

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Box low
Box high
Human shoulder
Human nose
Human brow

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Time [sec]Figure 3: Horizontal velocity of the hand (the horizontal component of the figure 2.)

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Box high
Human shoulder
Human nose
Human brow

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Vertical velocity [m/s]out and touching the other person. Even a simple reaching motionof a humanoid robot has not been studied with respect to how thechange of its properties due to social situations affects the impression of a subject toward the robot. As an extreme case, the present
paper models the motion difference between two cases in which a
subject touches another person or an inanimate object through observing the subject’s behavior. We then examine how the presenceof the motion diversity in an android motion influences the impression toward the android. In a psychological experiment, as a third
party, subjects watch an android touch a person and report theirimpressions.

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Time [sec]Figure 4: Vertical velocity of the hand (the vertical componentof the figure 2.)

Desired hand position
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Box high
Human shoulder
Human nose
Human brow

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Human nose
Human brow

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(a) Horizontal velocity.

Ballistic motion

Desired hand position

Time [sec](b) Vertical velocity.

Figure 5: Example of a subject’s hand velocity (subject 2).
Feedback motion
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Box low
Box high
Human shoulder
Human nose
Human brow

Ballistic motion

Figure 7: Model of variation of return motion.

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Human nose
Human brow

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Figure 6: Example of a subject’s hand velocity (subject 3).

ject. However, if the feature is not common among the subjects, it
may be difficult to obtain a common impression towards an android
in the later experiment. Therefore, we attempt to find a feature thatis shared by the majority of the subjects.
First, we calculate the absolute value of the hand velocity in order to facilitate the analysis. The trajectory of the hand positionis smoothed by a low-pass filter, and the velocity is calculated byforward differences. We investigate the difference in the velocity
profiles. As an example, the results for a typical subject are shownin Figure 2. Each plot is the absolute value of the velocity of thehand and is shifted in time so that the times of the first peaks are thesame. In each plot, the first bell-shaped curve indicates the reachingout motion, and the second bell-shaped curve indicates the returning motion. The following features were found to exist the data foreach subject.

returning phase has a peak before the maximum peak. Other examples of the horizontal and vertical components are shown in Figures
5 and 6. We can also find a similar profile of the horizontal component in these examples.
This feature appears six times among the 14 trials of the impersonal case and 18 times among the 21 trials of the interpersonalcase. In other words, this feature appears more often in the interpersonal case than in the impersonal case. Although there is no
statistically significant difference between the two cases because
the number of the subjects is not sufficient, we focus on this feature in order to differentiate the interpersonal and impersonal cases.
Comparing the horizontal and vertical components, the time to start
increasing the vertical velocity is always later than the time to start
increasing the horizontal velocity. There is a tendency for this timedelay to be larger in interpersonal cases than in impersonal cases.
These results suggest that, in the interpersonal case, when the subjects returned their hands, they moved their hands horizontally at
first and then brought their hands down, whereas, in the impersonal case, subjects brought their hands down from the beginning.
It is generally thought that a person moves his/her arm by controlling his/her hand position initially with feedback control and thenmoves his/her arm in a ballistic trajectory. This difference in motion can be modeled as the difference of desired hand position of
feedback control in the space close to another person (Figure 7). To
put it more concretely:• In the impersonal case, the desired hand position is set suchthat the hand can be returned in the fastest path (Figure 7,
top).

• The velocity profile in the reaching phase forms a unimodal,
bell-shaped curve that does not depend on the relationships(subject-person and subject-object).

• In the interpersonal case, the desired hand position is set suchthat the hand can move from the space in proximity to theother person along the fastest path (Figure 7, bottom).

• The velocity profile in the returning phase varies dependingon the relationships.
There were no remarkable differences in motion among the subjects that were familiar with the experimenter and the subjects thatwere not familiar with the experimenter. In order to examine thereturning phase in detail, the horizontal and vertical componentsof the velocity are calculated. Figures 3 and 4 show the absolutevalue of the horizontal and vertical components, respectively. In allcases, the profile of the vertical component in the returning phase
is a single-peak shape. This characteristic is common among all
subjects. Moreover, the profile of the horizontal component in the

Although this model is specific to the motion for touching anotherperson or a box, this model can be taken as a model of humanmotion diversity due to differences in social situation. In the next
section, we examine the influence of the model on the impressionof an android.

3.

EXPERIMENTS

3.1

Repliee Q2 android

Figure 10: Objects and persons in the video stimuli.

Figure 8: “Repliee Q2” android.

Figure 9: Android motions generated based on the constructed
model.

Figure 8 shows the Repliee Q2 android used in the experiment.
The android is modeled after a Japanese woman, the standing heightof which is approximately 160 cm. The skin is composed of a kindof silicone that feels like human skin. The android is driven bypneumatic actuators that give it 42 degrees of freedom from thewaist up. The legs and feet are not powered. The android can neither stand up nor move from a chair. The joints driven by the pneumatic actuator has mechanical flexibility in the control thanks to thehigh compressibility of air. The flexibility of the joints makes forsafer interaction, with movements that are generally smoother thanthose of other similar systems. The complicated dynamics of the
air actuator make executing the trajectory tracking control difficult.

3.2

MethodWe implemented the motion variation based on the proposedmodel in the Repliee Q2 android and investigated the impression
toward the android from a third-person viewpoint in psychologicalexperiments. We showed video recordings of the android motions
to subjects and asked the subjects impressions toward the android.
Figure 9 shows the android motion generated based on the proposedmodel. The top of the figure shows the motion in which the handis returned along the fastest path (motion M1). The bottom panel
shows the motion in which the hand leaves from the space near
the other person along the fastest path (motion M2). The motionof reaching out was implemented according to the average motionof the subjects’ reaching motions observed in the experiment described in Section 2. It is difficult to implement a quick and smooth
motion in the android with a simple feedback control because thejoints are driven by flexible pneumatic actuators. In order to avoid

Table 1: Experimental conditions.
Android A
Android B
Android C
Towards object Motion M1 Motion M2 Motion M1
Towards person Motion M1 Motion M2 Motion M2

this difficulty, we implemented the motions in the android so thatthe speed of motion is slow. The video stimuli were made by playing videos of the android with slow motion at fast speed.
In order to examine the influence of the motion diversity on theimpression toward the android, we prepared three types of android,as shown in Table 1. Three androids reach out and touch persons
and inanimate objects in different manners. The android in Condition A (android A) touches persons and objects with motion M1.
The android in Condition B (android B) touches persons and objects with motion M2. The android in Condition C (android C)
touches objects with motion M1 and persons with motion M2. Conditions A and B are used to examine the impressions with respect tothe androids without motion diversity, and Condition C is used to
examine the impressions with respect to the androids with motion
diversity. When the target is a person, the android touches the leftshoulder of the person sitting in a face-to-face position.
In each condition, a subject is presented six android motions toreport the impression. The android touches three objects (a calendar, a video camera, and a small shelf) and three male persons once
for each target. The six targets are shown in Figure 10. The video
stimulus is composed of a video recording of the android motion
and a video recording of the target. The video of each motion is fiveseconds long. In each condition, six motions were randomly presented to a subject with a constraint in which the motion of touching an object and the motion of touching a person were alternately
presented. In order to eliminate memory effect and aftereffect, ablank image was presented for two seconds between the videos, as
shown in Figure 11.
We designed a questionnaire using a five-point Likert scale with
1 = strongly disagree, 3 = neutral, and 5 = strongly agree. The
aim of the questionnaire is to ask the impression of the android’s
human-like nature; therefore, the questionnaire asked how the android is “humanlike.” It is, however, possible that the variationin the arm trajectories does not influence the impression on thehuman-likeness. We then prepared other six items in the questionnaire, which are likely influenced by the variation in the arm
trajectories. The items are “the android is (1) polite, (2) accurate,(3) intellectual, (4) conscientious, (5) friendly, (6) graceful, and (7)humanlike.” The items are listed in random order in order to avoid
the order effect, except for “humanlike,” which always appears at
the end of the questionnaire, because an answer to the item “humanlike” is likely to influence the responses to the other items.

StartBlank image*

Totally six movies of
the android motion

Android motion

**

5

**

5 sec

Time

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Android motion
2 sec

Blank image
5 sec
2 sec

...

Android A
Android C* p<0.1** p<0.05

Blank image

2 sec

Average score

Computerscreen3

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Figure 11: Procedure to present the video stimuli.
1

0

3.3

Experiment 1: comparing Conditions A
and C

At first, we first compared Conditions A and C in order to investigate the influence of the presence of motion diversity in the
android. The expectation is that the comparison of the impressionsof the human-like nature results in the following:

PoliteGraceful

Humanlike

Figure 12: Results of questionnaire about impression of androids A and C.

**
5

Android C > Android A.

Android A
Android B
Android C** p<0.05

Average score

4

3

2

1

0

The subjects were twenty-four university students (nineteen males
and five females) who were familiar with the Repliee Q2 android.
Each subject participated in both conditions, although the order ofthe conditions was changed randomly. The subject answered thequestionnaire after every condition was presented.
The average scores of the impressions are shown in Figure 12.
A paired t-test revealed significant differences (p < 0.05) in two
conditions for the items of “polite” and “graceful”, although there
was no significant difference for the item “humanlike.” The android behavior in which the hand quickly moves from the spacein proximity to the other person likely gave an impression that the
android carefully and deliberately touches the other person. It isinferred that the subjects thought that the android had an intentionof touching the other person carefully. It is, therefore, that the subjects thought that the android C is politer and more graceful. It canbe also said that the subjects were consciously or subconsciously
aware that the android C changed the hand trajectory from the factthat there are significant differences for some items.
Here, we consider the difference between androids A and C. In
Condition C, the android’s arm trajectory varies according to theandroid-target relationship, and in Condition A, the android’s arm
trajectory does not vary according to the android-target relationship. Another difference is that, in Condition C, the android shows
motion M2, which is not the case in Condition A. In other words,
there is a possibility that the presence of motion M2 produced different impressions. In order to show that the different impressions
are caused by the difference in social situation, it is necessary to
examine the influence of motion M2. Therefore, in the next session, we conducted an additional experiment to assess the android
in Condition B.

Accurate Intellectual Conscientious Friendly

PoliteAccurate Intellectual Conscientious Friendly

Graceful Humanlike

Figure 13: Results of questionnaire about impression of androids A, B, and C.

3.4

Experiment 2: comparing Conditions A,
B, and C

The subjects in this experiment were twelve of twenty-four subjects who participated in experiment 1. They were nine males andthree females. Each subject was presented the android B and answered the questionnaire about it. The expectation is that the comparison of the impressions of the human-like nature results in thefollowing:
Android C > Android A, Android B.
The average scores of the impressions toward android B are shownin Figure 13 by adding the result to Figure 12. Ryan’s multiple
comparison test revealed a significant difference (p < 0.05) between androids A and C for the item “graceful.” This is the same
result as the one obtained in the experiment 1. Contrary to our
expectation, however, there was no significant difference between
androids B and C.
We then considered the influence of the order of stimulus presentation. The subjects participated in experiment 2 assessed inorder of conditions A, C, and B or C, A, and B. Hereinafter, Case
O1 and Case O2 indicate the order of A→C→B and C→A→B,
respectively. A repeated measures two-way ANOVA with a factor
of condition order and a factor of android motion was conducted.

** p<0.05
52

0PoliteGraceful Humanlike

Figure 14: Impressions of subjects assessed in order of Conditions A, C, and B.
**** p<0.1** p<0.05*

Android A
Android B
Android C

*

5

**

Average score

4

3

2

1

Polite3.5

Accurate Intellectual Conscientious Friendly0

The difference from the impressions towards the android presented
right before was increased for the subjects. Ryan’s multiple comparison test revealed several significant differences at the 5% level
among androids A, B, and C as shown in Figures 14 and 15. In
particular, as expected, the score of “humanlike” for android C issignificantly larger than that for android B in Case O1. In Case O2,
the subjects thought the android which touched anything with the
motion M2 was more deliberate and careful than the android which
touched anything with the motion M1. Furthermore, it is likely that
this careful motion gave an impression that the android B was morehumanlike than the android A in Case O2. However, the subjects
thought the android C with motion variation was more humanlike
than the android B when the android C was presented just after the
android B in Case O1. It is possible that the subjects think the android with the motion variation is more humanlike than the android
with only the careful motion.

3

1• The scores obtained in the condition right after Condition C
are smaller than those in Condition C.
• The scores obtained in the condition right after Condition A
are larger than those in Condition A.

Android A
Android B **Android C

4

Average score

There were significant interactions at the 5% level for the items of“intellectual”, “friendly”, and “humanlike” and at the 10% level
for the item of “conscientious.” It is possible that the effect of theandroid motion on the impression score depends on the order ofconditions.
We divided the twelve subjects into subjects who participated inCase O1 (seven persons) and subjects who in Case O2 (five persons) and analyzed their impression scores. The average impression scores obtained in Cases O1 and O2 are shown in Figures 14
and 15, respectively. For each item, three conditions are rearrangedin the order of presentation. Two tendencies can be seen in thesefigures:Accurate Intellectual Conscientious Friendly

Graceful

Humanlike

Summary

The experimental results showed that the diversity of the android
motion enhances the impression of human-like nature toward theandroid under the influence of the order of stimulus presentation,although the expected result (i.e., android C is more humanlike thanandroids A and B) was not obtained. The number of subjects who
participated in the experiments was too few to compare the three
conditions. The expected effect of the motion diversity may beshown by an experiment with a larger number of subjects.
As an example of motion diversity, the present paper examinedmotion variation in which the desired hand position of feedback
control varies in two ways when the subject returns his/her hand
after touching a target. In addition, the social relationship, whichcauses this variation, was also designed to be varied in two cases,that is, android-person and android-object relationships. This is a
simple example of diversity. However, more complicated motion
variation can be designed, for example, by changing the causes ofthe variation. It is inferred that complicated variation has a different influence on the impression, although there are appropriate
variations for enhancing the human-like nature. Further investigation is necessary in order to clarify what motion diversity makes
the android humanlike.
In Section 2, we assumed that the variation of the subject’s arm
motion is caused by the social relationship between the subject andthe target. However, the subconscious motion variation was notverified to be due to the social situation. There is another possibility, i.e., that the variation is, for example, due to the hardness ofthe target, such as a hard box or a soft human body. In addition,

Figure 15: Impressions of subjects assessed in order of Conditions C, A, and B.

it was not verified that the subjects in Section 3 actually attributed
the cause of motion variation to the social situation, although the
motion variation conditionally enhanced the impression of the android’s human-like nature. In other words, it is not clear that the
subjects think the android C socially behaves like human beings.
One possible design of an experiment is to compare with the android which has same motions but different motion variation, thatis, the android which touches objects with motion M2 and persons
with motion M1 (this manner is opposite to the android C). If thisandroid is less humanlike than the android C, the motion variation
which is congruent with that of human subjects shown in Section
2 contributes the human-likeness of the android. However, further
investigation is necessary to verify whether the social relationshipcaused the arm motion variation observed in Section 2 and the different impressions toward the android obtained in Section 3.

4.

CONCLUSION

We hypothesized that a motion diversity that is not related toa subject’s intention and can be consciously controlled influences
the humanlike impression of the subject, and we assumed that thismotion diversity makes the android more humanlike. In order toverify this hypothesis, we constructed a model of the motion diver-sity through the observation of a person’s motion. We examinedthe variation in a motion of reaching out and touching another person, which occurred in different social relationships between thesubject and the other person (or object). The experimental results
showed that the modeled motion diversity conditionally influences
the impression toward the android.
The results of the present paper are specific to the android’s motion of reaching out and touching a person. The present study is a
first step in the exploration of the principles for providing naturalrobot behaviors. The results revealed that a phenomenon whereby
motion diversity influences the impression of a subject can be seenat least in certain motions of a very humanlike robot. Based onthese results, it is possible to examine which aspects of the robot’s
appearance and motion are affected by this phenomenon. This
exploration will help to clarify the principles underlying natural
human-robot communication.
From the viewpoint of the robot motion design, a motion diversity model is also useful. Several studies have proposed a methodby which to implement humanlike motion in a humanoid robot bycopying human motion as measured by a motion capture system tothe robot [12, 9, 7]. In order to make a robot motion more humanlike, it is necessary to implement a humanlike motion variation.
However, it is not necessary to copy all human motions. This humanlike motion variation can be easily generated from an original
motion by the motion diversity model.

5.

ACKNOWLEDGEMENTS

The android robot Repliee Q2 was developed in collaboration
with Kokoro Company, Ltd.

6.

REFERENCES[1] B. Bodenheimer, A. V. Shleyfman, and J. K. Hodgins. The
effects of noise on the perception of animated humanrunning. In Proceedings of Eurographics Animation
Workshop, pages 53–63, 1999.
[2] T. Flash and N. Hogan. The coordination of arm movements:
An experimentally confirmed mathematical model. Journalof Neuroscience, 5:1688–1703, 1985.
[3] H. Ishiguro. Android science -toward a new
cross-interdisciplinary framework. In Proceedings of theInternational Symposium of Robotics Research, 2005.
[4] P. Jacob and M. Jeannerod. The motor theory of social
cognition: a critique. Trends in Cognitive Sciences,9(1):21–25, 2005.

[5] T. Kashima and Y. Isurugi. Trajectory formation based on
physiological characteristics of skeletal muscles. Biological
Cybernetics, 78(6):413–422, 1998.
[6] M. Kawato. Optimization and learning in neural networks forformation and control of coordinated movement. In D. M. D
and S. Kornblum, editors, Attention and performance XIV,
pages 821–849. MIT Press, 1992.
[7] D. Matsui, T. Minato, K. F. MacDorman, and H. Ishiguro.
Generating natural motion in an android by mapping humanmotion. In Proceedings of the IEEE/RSJ International
Conference on Intelligent Robot Systems, pages 1089–1096,
Edmonton, Alberta, Canada, 2005.
[8] H. Miyamoto, E. Nakano, D. M. Wolpert, and M. Kawato.
Tops (task optimization in the presence of signal-dependent
noise) model. Systems and Computers in Japan, 35:48–58,
2004.
[9] S. Nakaoka, A. Nakazawa, K. Yokoi, H. Hirukawa, andK. Ikeuchi. Generating whole body motions for a bipedhumanoid robot from captured human dances. In
Proceedings of the 2003 IEEE International Conference on
Robotics and Automation, pages 3905–3910, Taipei, Taiwan,
2003.
[10] C. Nass, J. Steuer, and E. Tauber. Computers are social
actors. In Proceedings of the ACM Conference on Human
Factors in Computing Systems, pages 72–78, 1994.
[11] K. Perlin. Real time responsive animation with personality.
IEEE Transactions on Visualization and Computer Graphics,
1(1):5–15, 1995.
[12] M. Riley, A. Ude, and C. G. Atkeson. Methods for motion
generation and interaction with a humanoid robot: Casestudies of dancing and catching. In Proceedings of AAAI and
CMU Workshop on Interactive Robotics and Entertainment,
2000.
[13] S. Schaal and D. Sternad. Origins and violations of the 2/3
power law in rhythmic 3d movements. Experimental Brain
Research, 136:60–72, 2001.
[14] E. Todorov and M. I. Jordan. Optimal feedback control as atheory of motor coordination. Nature Neuroscience,5(11):1226–1235, 2002.
[15] Y. Uno, M. Kawato, and R. Suzuki. Formation and control of
optical trajectory in human multi-joint arm movement minimim torque-change model. Biological Cybernetics,
61:89–101, 1989.